Similarity-based scaling networks for capacitive radio frequency discharge plasmas

Huihui Wang, Dong Yang*, Bocong Zheng, John P. Verboncoeur, Yangyang Fu*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

We demonstrate similarity-based scaling networks for capacitive radio frequency (RF) plasmas, which extensively correlate discharge characteristics under varied conditions, incorporating the transition from original to similarity states. Based on fully kinetic particle-in-cell simulations, similar RF discharges in argon are demonstrated with three external control parameters (gas pressure, gap distance, and driving frequency) simultaneously tuned. A complete set of scaling pathways regarding fundamental discharge parameters is obtained, from which each plasma state finds its neighboring node with only one control parameter tuned. The results from this study provide a promising strategy for plasma multi-parameter mapping, enabling effective cross-comparisons, prediction, and manipulation of RF discharge plasmas.

Original languageEnglish
Article number095001
JournalAIP Advances
Volume13
Issue number9
DOIs
Publication statusPublished - 1 Sept 2023

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